


'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase_			:  Any										=   {
    """configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase_			:  List[str]										=   [
     """GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """GPTBigCodeForSequenceClassification""",
     """GPTBigCodeForTokenClassification""",
     """GPTBigCodeForCausalLM""",
     """GPTBigCodeModel""",
     """GPTBigCodePreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_bigcode import (
      GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTBigCodeForCausalLM,
      GPTBigCodeForSequenceClassification,
      GPTBigCodeForTokenClassification,
      GPTBigCodeModel,
      GPTBigCodePreTrainedModel,
  )


else:
 import sys

 UpperCAmelCase_			:  Any										=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







"""simple docstring"""



import os



def 	_lowerCamelCase(	a = "matrix.txt"				):
       with open(os.path.join(os.path.dirname(a				)   ,    a				)				) as in_file:
              __a       =    in_file.read()

       __a       =    [[int(a				) for cell in row.split(","				)] for row in data.strip().splitlines()]
       __a       =    [[0 for cell in row] for row in grid]
       __a       =    len(grid[0]				)

       __a       =    [[0 for i in range(a				)] for j in range(a				)]
       __a       =    grid[0][0]
       for i in range(1   ,    a				):
              __a       =    grid[0][i] + dp[0][i - 1]
       for i in range(1   ,    a				):
              __a       =    grid[i][0] + dp[i - 1][0]

       for i in range(1   ,    a				):
              for j in range(1   ,    a				):
                     __a       =    grid[i][j] + min(dp[i - 1][j]   ,    dp[i][j - 1]				)

       return dp[-1][-1]


if __name__ == "__main__":
   print(F'''{solution() = }''')
